Instructions to use semy/hf-model-1-0-0 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use semy/hf-model-1-0-0 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="semy/hf-model-1-0-0")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("semy/hf-model-1-0-0") model = AutoModelForSequenceClassification.from_pretrained("semy/hf-model-1-0-0", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from semy/hf-model-1-0-0: direct link, hf CLI and curl.
- Browser
- Download file 3.44 kB
-
https://huggingface.co/semy/hf-model-1-0-0/resolve/main/training_args.bin
- Command line
-
hf download hf://semy/hf-model-1-0-0/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/semy/hf-model-1-0-0/resolve/main/training_args.bin
3.44 kB
- Xet hash:
- bf4a480574933acca1964434a7e1b90a392ce66f618f8cf7ee3089d34e2a27cc
- Size of remote file:
- 3.44 kB
- SHA256:
- ccc4b0a0bb6f76b932309b13fdcd94125835914a5b9f6ea79473c498a6b2864d
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